With the explosive growth of the World Wide Web, the public is gaining access to massive
amounts of information. However, locating needed and relevant information remains a …

In many areas of commerce, government, academia, and hospitals, large collections of
digital images are being created. Many of these collections are the product of digitizing …

This paper describes a new hierarchical approach to content-based image retrieval called
the" customized-queries" approach (CQA). Contrary to the single feature vector approach …

Semantic Similarity relates to computing the similarity between conceptually similar but not
necessarily lexically similar terms. Typically, semantic similarity is computed by mapping …

Significant time and effort has been devoted to finding feature representations of images in
databases in order to enable content-based image retrieval (CBIR). Relevance feedback is …

A database of visual images includes metadata having, for a particular image, at least one
entry specifying: a part of that image, another stored image, and a measure S abi of the …

The amount of audiovisual information available in digital format has grown exponentially in
recent years. Gigabytes of new images, audio and video clips are generated and stored …

Major search engines such as Hotbot (http://www. hotbot. com) help us find text on the Web,
but typically have few or no capabilities for finding visual media. Yet many Web users, such …

Self-Organising Maps (SOMs) can be used in implementing a powerful relevance feedback
mechanism for Content-Based Image Retrieval (CBIR). This paper introduces the PicSOM …

Content-based image retrieval systems require the development of relevance feedback
mechanisms that allow the user to progressively refine the system's response to a query. In …